scholarly journals Emergence of the Affect from the Variation in the Whole-Brain Flow of Information

2019 ◽  
Vol 10 (1) ◽  
pp. 8
Author(s):  
Soheil Keshmiri ◽  
Masahiro Shiomi ◽  
Hiroshi Ishiguro
Keyword(s):  
Information Flow ◽  
Cortical Neurons ◽  
Large Scale ◽  
Brain Activation ◽  
Brain Regions ◽  
Neural Basis ◽  
Whole Brain ◽  
Affect States ◽  
Flow Of Information ◽  
The Brain

Over the past few decades, the quest for discovering the brain substrates of the affect to understand the underlying neural basis of the human’s emotions has resulted in substantial and yet contrasting results. Whereas some point at distinct and independent brain systems for the Positive and Negative affects, others propose the presence of flexible brain regions. In this respect, there are two factors that are common among these previous studies. First, they all focused on the change in brain activation, thereby neglecting the findings that indicate that the stimuli with equivalent sensory and behavioral processing demands may not necessarily result in differential brain activation. Second, they did not take into consideration the brain regional interactivity and the findings that identify that the signals from individual cortical neurons are shared across multiple areas and thus concurrently contribute to multiple functional pathways. To address these limitations, we performed Granger causal analysis on the electroencephalography (EEG) recordings of the human subjects who watched movie clips that elicited Negative, Neutral, and Positive affects. This allowed us to look beyond the brain regional activation in isolation to investigate whether the brain regional interactivity can provide further insights for understanding the neural substrates of the affect. Our results indicated that the differential affect states emerged from subtle variation in information flow of the brain cortical regions that were in both hemispheres. They also showed that these regions that were rather common between affect states than distinct to a specific affect were characterized with both short- as well as long-range information flow. This provided evidence for the presence of simultaneous integration and differentiation in the brain functioning that leads to the emergence of different affects. These results are in line with the findings on the presence of intrinsic large-scale interacting brain networks that underlie the production of psychological events. These findings can help advance our understanding of the neural basis of the human’s emotions by identifying the signatures of differential affect in subtle variation that occurs in the whole-brain cortical flow of information.

Information Processing in the Mental Workspace Is Fundamentally Distributed

2016 ◽  
Vol 28 (2) ◽  
pp. 295-307 ◽  
Author(s):  
Alexander Schlegel ◽  
Prescott Alexander ◽  
Peter U. Tse
Keyword(s):  
Information Processing ◽  
Information Flow ◽  
The Novel ◽  
Neural Basis ◽  
Distributed Information ◽  
Network Support ◽  
Component Processes ◽  
High Level ◽  
Flow Of Information ◽  
The Brain

The brain is a complex, interconnected information processing network. In humans, this network supports a mental workspace that enables high-level abilities such as scientific and artistic creativity. Do the component processes underlying these abilities occur in discrete anatomical modules, or are they distributed widely throughout the brain? How does the flow of information within this network support specific cognitive functions? Current approaches have limited ability to answer such questions. Here, we report novel multivariate methods to analyze information flow within the mental workspace during visual imagery manipulation. We find that mental imagery entails distributed information flow and shared representations throughout the cortex. These findings challenge existing, anatomically modular models of the neural basis of higher-order mental functions, suggesting that such processes may occur at least in part at a fundamentally distributed level of organization. The novel methods we report may be useful in studying other similarly complex, high-level informational processes.

scholarly journals Heterogeneity of EEG resting-state brain networks in absolute pitch

2020 ◽  
Author(s):  
Marielle Greber ◽  
Carina Klein ◽  
Simon Leipold ◽  
Silvano Sele ◽  
Lutz Jäncke
Keyword(s):  
Functional Connectivity ◽  
Auditory Cortex ◽  
Resting State ◽  
Large Scale ◽  
Absolute Pitch ◽  
Brain Regions ◽  
Brain Network ◽  
Higher Order ◽  
Neural Basis ◽  
Whole Brain

AbstractThe neural basis of absolute pitch (AP), the ability to effortlessly identify a musical tone without an external reference, is poorly understood. One of the key questions is whether perceptual or cognitive processes underlie the phenomenon as both sensory and higher-order brain regions have been associated with AP. One approach to elucidate the neural underpinnings of a specific expertise is the examination of resting-state networks.Thus, in this paper, we report a comprehensive functional network analysis of intracranial resting-state EEG data in a large sample of AP musicians (n = 54) and non-AP musicians (n = 51). We adopted two analysis approaches: First, we applied an ROI-based analysis to examine the connectivity between the auditory cortex and the dorsolateral prefrontal cortex (DLPFC) using several established functional connectivity measures. This analysis is a replication of a previous study which reported increased connectivity between these two regions in AP musicians. Second, we performed a whole-brain network-based analysis on the same functional connectivity measures to gain a more complete picture of the brain regions involved in a possibly large-scale network supporting AP ability.In our sample, the ROI-based analysis did not provide evidence for an AP-specific connectivity increase between the auditory cortex and the DLPFC. In contrast, the whole-brain analysis revealed three networks with increased connectivity in AP musicians comprising nodes in frontal, temporal, subcortical, and occipital areas. Commonalities of the networks were found in both sensory and higher-order brain regions of the perisylvian area. Further research will be needed to confirm these exploratory results.

scholarly journals The Neural Basis of Motivational Influences on Cognitive Control

2017 ◽  
Author(s):  
Cameron Parro ◽  
Matthew L Dixon ◽  
Kalina Christoff
Keyword(s):  
Cognitive Control ◽  
Large Scale ◽  
Functional Neuroimaging ◽  
Meta Analysis ◽  
Premotor Cortex ◽  
Likelihood Estimation ◽  
Brain Regions ◽  
Control Mechanisms ◽  
Neural Basis ◽  
The Brain

AbstractCognitive control mechanisms support the deliberate regulation of thought and behavior based on current goals. Recent work suggests that motivational incentives improve cognitive control, and has begun to elucidate the brain regions that may support this effect. Here, we conducted a quantitative meta-analysis of neuroimaging studies of motivated cognitive control using activation likelihood estimation (ALE) and Neurosynth in order to delineate the brain regions that are consistently activated across studies. The analysis included functional neuroimaging studies that investigated changes in brain activation during cognitive control tasks when reward incentives were present versus absent. The ALE analysis revealed consistent recruitment in regions associated with the frontoparietal control network including the inferior frontal sulcus (IFS) and intraparietal sulcus (IPS), as well as consistent recruitment in regions associated with the salience network including the anterior insula and anterior mid-cingulate cortex (aMCC). A large-scale exploratory meta-analysis using Neurosynth replicated the ALE results, and also identified the caudate nucleus, nucleus accumbens, medial thalamus, inferior frontal junction/premotor cortex (IFJ/PMC), and hippocampus. Finally, we conducted separate ALE analyses to compare recruitment during cue and target periods, which tap into proactive engagement of rule-outcome associations, and the mobilization of appropriate viscero-motor states to execute a response, respectively. We found that largely distinct sets of brain regions are recruited during cue and target periods. Altogether, these findings suggest that flexible interactions between frontoparietal, salience, and dopaminergic midbrain-striatal networks may allow control demands to be precisely tailored based on expected value.

scholarly journals Large-scale intrinsic connectivity is consistent across varying task demands

2018 ◽  
Author(s):  
Paulina Kieliba ◽  
Sasidhar Madugula ◽  
Nicola Filippini ◽  
Eugene P. Duff ◽  
Tamar R. Makin
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Large Scale ◽  
Brain Activation ◽  
Whole Brain ◽  
Activation Patterns ◽  
Intrinsic Connectivity ◽  
Connectivity Patterns ◽  
Brain Functional Connectivity ◽  
The Brain

AbstractMeasuring whole-brain functional connectivity patterns based on task-free (‘restingstate’) spontaneous fluctuations in the functional MRI (fMRI) signal is a standard approach to probing habitual brain states, independent of task-specific context. This view is supported by spatial correspondence between task- and rest-derived connectivity networks. Yet, it remains unclear whether intrinsic connectivity observed in a resting-state acquisitions is persistent during task. Here, we sought to determine how changes in ongoing brain activation, elicited by task performance, impact the integrity of whole-brain functional connectivity patterns. We employed a ‘steadystates’ paradigm, in which participants continuously executed a specific task (without baseline periods). Participants underwent separate task-based (visual, motor and visuomotor) or task-free (resting) steady-state scans, each performed over a 5-minute period. This unique design allowed us to apply a set of traditional resting-state analyses to various task-states. In addition, a classical fMRI block-design was employed to identify individualized brain activation patterns for each task, allowing to characterize how differing activation patterns across the steady-states impact whole-brain intrinsic connectivity patterns. By examining correlations across segregated brain regions (nodes) and the whole brain (using independent component analysis), we show that the whole-brain network architecture characteristic of the resting-state is robustly preserved across different steady-task states, despite striking inter-task changes in brain activation (signal amplitude). Subtler changes in functional connectivity were detected locally, within the active networks. Together, we show that intrinsic connectivity underlying the canonical resting-state networks is relatively stable even when participants are engaged in different tasks and is not limited to the resting-state.New and NoteworthyDoes intrinsic functional connectivity (FC) reflect the canonical or transient state of the brain? We tested the consistency of the intrinsic connectivity networks across different task-conditions. We show that despite local changes in connectivity, at the whole-brain level there is little modulation in FC patterns, despite profound and large-scale activation changes. We therefore conclude that intrinsic FC largely reflects the a priori habitual state of the brain, independent of the specific cognitive context.

scholarly journals Rethinking brain-wide interactions through multi-region “network of networks” models

2020 ◽  
Author(s):  
Matthew Perich ◽  
Kanaka Rajan
Keyword(s):  
Recent Work ◽  
Neural Control ◽  
Large Scale ◽  
Brain Regions ◽  
Interconnected Network ◽  
Neural Basis ◽  
Theoretical Approaches ◽  
Neural Populations ◽  
The Brain ◽  
Network Of Networks

The neural control of behavior is distributed across many functionally and anatomically distinct brain regions even in small nervous systems. While classical neuroscience models treated these regions as a set of hierarchically isolated nodes, the brain comprises a recurrently interconnected network in which each region is intimately modulated by many others. Uncovering these interactions is now possible through experimental techniques that access large neural populations from many brain regions simultaneously. Harnessing these large-scale datasets, however, requires new theoretical approaches. Here, we review recent work to understand brain-wide interactions using multi-region "network of networks" models and discuss how they can guide future experiments. We also emphasize the importance of multi-region recordings, and posit that studying individual components in isolation will be insufficient to understand the neural basis of behavior.

scholarly journals Decreased Directed Functional Connectivity in the Psychedelic State

2019 ◽  
Author(s):  
Lionel Barnett ◽  
Suresh D. Muthukumaraswamy ◽  
Robin L. Carhart-Harris ◽  
Anil K. Seth
Keyword(s):  
Functional Connectivity ◽  
Information Flow ◽  
Large Scale ◽  
Anticonvulsant Drug ◽  
Neural Dynamics ◽  
General Interest ◽  
Neural Basis ◽  
Time Resolved ◽  
Neuroimaging Data ◽  
The Brain

AbstractNeuroimaging studies of the psychedelic state offer a unique window onto the neural basis of conscious perception and selfhood. Despite well understood pharmacological mechanisms of action, the large-scale changes in neural dynamics induced by psychedelic compounds remain poorly understood. Using source-localised, steady-state MEG recordings, we describe changes in functional connectivity following the controlled administration of LSD, psilocybin and low-dose ketamine, as well as, for comparison, the (non-psychedelic) anticonvulsant drug tiagabine. We compare both undirected and directed measures of functional connectivity between placebo and drug conditions. We observe a general decrease in directed functional connectivity for all three psychedelics, as measured by Granger causality, throughout the brain. These data support the view that the psychedelic state involves a breakdown in patterns of functional organisation or information flow in the brain. In the case of LSD, the decrease in directed functional connectivity is coupled with an increase in undirected functional connectivity, which we measure using correlation and coherence. This surprising opposite movement of directed and undirected measures is of more general interest for functional connectivity analyses, which we interpret using analytical modelling. Overall, our results uncover the neural dynamics of information flow in the psychedelic state, and highlight the importance of comparing multiple measures of functional connectivity when analysing time-resolved neuroimaging data.

scholarly journals Entropy of the Multi-Channel EEG Recordings Identifies the Distributed Signatures of Negative, Neutral and Positive Affect in Whole-Brain Variability

Entropy ◽  
2019 ◽  
Vol 21 (12) ◽  
pp. 1228 ◽  
Author(s):  
Soheil Keshmiri ◽  
Masahiro Shiomi ◽  
Hiroshi Ishiguro
Keyword(s):  
Positive Affect ◽  
Fundamental Property ◽  
Brain Activation ◽  
Neural Substrates ◽  
Brain Regions ◽  
Subjective Experiences ◽  
Whole Brain ◽  
Eeg Recordings ◽  
Negative Feelings ◽  
The Brain

Individuals’ ability to express their subjective experiences in terms of such attributes as pleasant/unpleasant or positive/negative feelings forms a fundamental property of their affect and emotion. However, neuroscientific findings on the underlying neural substrates of the affect appear to be inconclusive with some reporting the presence of distinct and independent brain systems and others identifying flexible and distributed brain regions. A common theme among these studies is the focus on the change in brain activation. As a result, they do not take into account the findings that indicate the brain activation and its information content does not necessarily modulate and that the stimuli with equivalent sensory and behavioural processing demands may not necessarily result in differential brain activation. In this article, we take a different stance on the analysis of the differential effect of the negative, neutral and positive affect on the brain functioning in which we look into the whole-brain variability: that is the change in the brain information processing measured in multiple distributed regions. For this purpose, we compute the entropy of individuals’ muti-channel EEG recordings who watched movie clips with differing affect. Our results suggest that the whole-brain variability significantly differentiates between the negative, neutral and positive affect. They also indicate that although some brain regions contribute more to such differences, it is the whole-brain variational pattern that results in their significantly above chance level prediction. These results imply that although the underlying brain substrates for negative, neutral and positive affect exhibit quantitatively differing degrees of variability, their differences are rather subtly encoded in the whole-brain variational patterns that are distributed across its entire activity.

scholarly journals Increased sensitivity to strong perturbations in a whole-brain model of LSD

2021 ◽  
Author(s):  
Beatrice M. Jobst ◽  
Selen Atasoy ◽  
Adrián Ponce-Alvarez ◽  
Ana Sanjuán ◽  
Leor Roseman ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
External Perturbation ◽  
Brain Regions ◽  
Lysergic Acid ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Whole Brain ◽  
Response Diversity ◽  
Brain States ◽  
The Brain

AbstractLysergic acid diethylamide (LSD) is a potent psychedelic drug, which has seen a revival in clinical and pharmacological research within recent years. Human neuroimaging studies have shown fundamental changes in brain-wide functional connectivity and an expansion of dynamical brain states, thus raising the question about a mechanistic explanation of the dynamics underlying these alterations. Here, we applied a novel perturbational approach based on a whole-brain computational model, which opens up the possibility to externally perturb different brain regions in silico and investigate differences in dynamical stability of different brain states, i.e. the dynamical response of a certain brain region to an external perturbation. After adjusting the whole-brain model parameters to reflect the dynamics of functional magnetic resonance imaging (fMRI) BOLD signals recorded under the influence of LSD or placebo, perturbations of different brain areas were simulated by either promoting or disrupting synchronization in the regarding brain region. After perturbation offset, we quantified the recovery characteristics of the brain area to its basal dynamical state with the Perturbational Integration Latency Index (PILI) and used this measure to distinguish between the two brain states. We found significant changes in dynamical complexity with consistently higher PILI values after LSD intake on a global level, which indicates a shift of the brain’s global working point further away from a stable equilibrium as compared to normal conditions. On a local level, we found that the largest differences were measured within the limbic network, the visual network and the default mode network. Additionally, we found a higher variability of PILI values across different brain regions after LSD intake, indicating higher response diversity under LSD after an external perturbation. Our results provide important new insights into the brain-wide dynamical changes underlying the psychedelic state - here provoked by LSD intake - and underline possible future clinical applications of psychedelic drugs in particular psychiatric disorders.HighlightsNovel offline perturbational method applied on functional magnetic resonance imaging (fMRI) data under the effect of lysergic acid diethylamide (LSD)Shift of brain’s global working point to more complex dynamics after LSD intakeConsistently longer recovery time after model perturbation under LSD influenceStrongest effects in resting state networks relevant for psychedelic experienceHigher response diversity across brain regions under LSD influence after an external in silico perturbation

scholarly journals Exploring the dynamic mechanisms of steady-state visual evoked potentials at the whole-brain level: evidence from a computational study

2021 ◽  
Author(s):  
Ge Zhang ◽  
Yan Cui ◽  
Yangsong Zhang ◽  
Hefei Cao ◽  
Guanyu Zhou ◽  
...  
Keyword(s):  
Steady State ◽  
Evoked Potentials ◽  
Visual Evoked Potentials ◽  
Large Scale ◽  
Whole Brain ◽  
Frequency Sensitivity ◽  
Dynamic Mechanisms ◽  
Brain Level ◽  
The Brain ◽  
Visual Evoked

AbstractPeriodic visual stimulation can induce stable steady-state visual evoked potentials (SSVEPs) distributed in multiple brain regions and has potential applications in both neural engineering and cognitive neuroscience. However, the underlying dynamic mechanisms of SSVEPs at the whole-brain level are still not completely understood. Here, we addressed this issue by simulating the rich dynamics of SSVEPs with a large-scale brain model designed with constraints of neuroimaging data acquired from the human brain. By eliciting activity of the occipital areas using an external periodic stimulus, our model was capable of replicating both the spatial distributions and response features of SSVEPs that were observed in experiments. In particular, we confirmed that alpha-band (8-12 Hz) stimulation could evoke stronger SSVEP responses; this frequency sensitivity was due to nonlinear resonance and could be modulated by endogenous factors in the brain. Interestingly, the stimulus-evoked brain networks also exhibited significant superiority in topological properties near this frequency-sensitivity range, and stronger SSVEP responses were demonstrated to be supported by more efficient functional connectivity at the neural activity level. These findings not only provide insights into the mechanistic understanding of SSVEPs at the whole-brain level but also indicate a bright future for large-scale brain modeling in characterizing the complicated dynamics and functions of the brain.

scholarly journals Message-Elicited Brain Response Moderates the Relationship Between Opportunities for Exposure to Anti-Smoking Messages and Message Recall

2019 ◽  
Vol 69 (6) ◽  
pp. 589-611
Author(s):  
Elissa C Kranzler ◽  
Ralf Schmälzle ◽  
Rui Pei ◽  
Robert C Hornik ◽  
Emily B Falk
Keyword(s):  
Large Scale ◽  
Communication Theory ◽  
Brain Regions ◽  
Message Processing ◽  
Memory Encoding ◽  
Brain Response ◽  
Real Cost ◽  
Social Processing ◽  
The Relationship ◽  
The Brain

Abstract Campaign success is contingent on adequate exposure; however, exposure opportunities (e.g., ad reach/frequency) are imperfect predictors of message recall. We hypothesized that the exposure-recall relationship would be contingent on message processing. We tested moderation hypotheses using 3 data sets pertinent to “The Real Cost” anti-smoking campaign: past 30-day ad recall from a rolling national survey of adolescents aged 13–17 (n = 5,110); ad-specific target rating points (TRPs), measuring ad reach and frequency; and ad-elicited response in brain regions implicated in social processing and memory encoding, from a separate adolescent sample aged 14–17 (n = 40). Average ad-level brain activation in these regions moderates the relationship between national TRPs and large-scale recall (p < .001), such that the positive exposure-recall relationship is more strongly observed for ads that elicit high levels of social processing and memory encoding in the brain. Findings advance communication theory by demonstrating conditional exposure effects, contingent on social and memory processes in the brain.

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